The long term goal of this project is to explain the mechanism of hypertonic urine formation in mammals by computer simulation. This goal has been achieved; we have developed a model that represents the structures of the kidney medulla and the membrane transport functions of those structures. The novel feature of this model is the incorporation of the known 3-dimensional structure of the medulla. Inclusion of this feature allows this model to predict concentrating effects in the renal inner medulla consistent with measurements made in experimental animals, and without invoking active transport of solutes from any of the tubules of the inner medulla. The present form of the model represents an hypothesis of hypertonic urine formation; in the next grant period we propose to test this hypothesis. The model solution predicts that there should be gradients of NaCl and urea both in the axial direction, a result extensively documented in the literature, and in the radial direction. The existence of radial NaCl gradients will be tested for by measurements in rats using electron microprobe techniques applied to blood vessels in the inner and outer medulla. Predicted radial gradients of urea in the inner medulla will be tested for by micropuncture; the latter technique will also be used to test for predicted radial NaCl gradients in the inner medulla between tubular fluid and capillary plasma, in instances where electron microprobe analysis would not be reliable. Although the model captures the 3-dimensional ordering of the medulla, it is not fully isomorphic in other respects that could reduce predicted concentrating ability. These effects will be introduced ; they include a) erythrocytes in the blood, b) non-ideal physical chemistry of concentrated NaCl and urea solutions, c) active transport of NaCl from inner medullary collecting ducts, and d) a medullary ray as a transition between the cortex and the outer stripe of the outer medulla. Finally we will continue work on the application of neural network techniques to increase the speed of solution of large nonlinear boundary value problems, like the 3-dimensional kidney model.